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A. Luna, M. L. Ortega, E. de la Fuente
THE INNER GALACTIC STRUCTURE TRACED BY MOLECULAR CLOUDS ASSOCIATED WITH ULTRACOMPACT HII REGIONS
Revista Mexicana de Astronomía y Astrofísica, vol. 34, 2008, pp. 127-128,
Instituto de Astronomía
México
Available in: http://www.redalyc.org/articulo.oa?id=57116170033
Revista Mexicana de Astronomía y Astrofísica,
ISSN (Printed Version): 0185-1101
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Instituto de Astronomía
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RevMexAA (Serie de Conferencias), 34, 127–128 (2008)
THE INNER GALACTIC STRUCTURE TRACED BY MOLECULAR
CLOUDS ASSOCIATED WITH ULTRA-COMPACT HII REGIONS
A. Luna,1 M. L. Ortega,2 and E. de la Fuente3
© 2008: Instituto de Astronomía, UNAM - IV Reunión sobre Astronomía Dinámica en Latinoamérica
Ed. Christine Allen, Alex Ruelas, & Ramachrisna Teixeira
RESUMEN
Estamos sometiendo a pruebas un método para determinar las distancias para una muestra de regiones HII ultracompactas con colores en IRAS y con detección de CS(J=2-1). La ambigüedad de las distancias cinemáticas
se resuelve mediante simulaciones Monte Carlo. Utilizando nubes moleculares sintéticas simulamos las distribuciones longitud heliocéntrica-radio (l-R) sobre el plano galáctico, y las proyecciones asociadas longitudvelocidadLSR (l-VLSR ). Se escoge la mejor distribución galáctica por comparación con los mapas observados
de CO. Se presentan resultados preliminares para el IV cuadrante galáctico.
ABSTRACT
We are testing a method to solve for the distances of a sample of ultra-compact (UC) HII regions with IRAS
colors and CS(J=2-1) detection. The ambiguity in their kinematical distances is solved using Monte-Carlo
simulations. We simulated heliocentric longitude-Radius (l-R) on Galactic plane distributions, and their respective longitude-VelocityLSR (l-VLSR ) projections using synthetic associated molecular clouds. The best
Galactic distribution is selected by comparison with observed CO maps. Preliminary results for the Galactic
quadrant IV are presented.
Key Words: Galaxy: disk — H II regions
1. METHODOLOGY
A testing to solve the distance ambiguity in the
inner galactic disk region using the sample of UC HII
regions with IRAS colors and CS(J=2-1) detection
(Bronfman, Nyman, & May 1996) is presented. Our
basic assumption is that every UC HII region must
be associated with a molecular cloud, and in such
case, the counterpart could be observed in CO maps.
Synthetic l-VLSR diagrams are generated from l-R
distributions of UC HII regions (Figure 1) where the
ambiguity in distance is solved selecting randomly
between near and far cases. The respective l-VLSR
distributions (Figure 2) were obtained considering:
(1) that the molecular interstellar medium at large
scales (∼ kpc) is optically thin, (2) a galactic rotation curve from Luna et al. (2006, overploted in Figure 1a), (3) the background spiral model of the spiral
pattern structure from Luna (2003, Figures 1a and
2b), (4) values for R =8.5 kpc and V =220 km s−1
according to the IAU recommendation. Further1 Instituto Nacional de Astrofı́sica, Óptica y Electrónica,
Apdo.
Postal 51 y 216, Tonantzintla, Puebla, Mexico
([email protected]).
2 Instituto
de Astronomı́a y Meteorologı́a, Dpto.
Fı́sica, CUCEI, Universidad de Guadalajara, México
([email protected]).
3 Colegio de Educación Profesional Técnica, CONALEPChipilo, Km 15.5, Carretera Federal Puebla-Atlixco, México
([email protected]).
more, the model is based on simple circular orbits,
differential rotation, and an inner radial velocity field
decreasing exponentially is added. Synthetic giant
molecular clouds (GMCs) are spherical with Gaussian intensity profiles and all the GMCs have the
same radial dimension, 250 pc. We propose to compare synthetic l-VLSR diagrams against observed CO
survey (Figure 2a, Dame, Hartmman, & Thadeuss
2001). The central 10 degrees that correspond to the
galactic center are excluded in the present analysis.
The outer Carina arm is used as a control reference,
locus at: l-VLSR diagrams −80 < l < −40 and 0 <
v < 50.
2. PRELIMINARY GENERAL RESULTS
The synthetic l-VLSR projection with good cross
correlation index (0.83, Figure 1c and 2c) was selected from a run of 1000 models where the distance
was randomly selected between the near and far possibilities with a normal distribution. The lowest correlation index (0.75) was obtained forcing the near
distance for the entire set of UC HII regions. The
best cross correlation between the numerical l-VLSR
projections and the observed map corresponds to the
far distance selection. This result shows that long
structures like spiral arms are predominant. The
Carina arm used as reference in all the models is
well reproduced in the l-VLSR diagrams. Random
127
128
LUNA, ORTEGA, & DE LA FUENTE
© 2008: Instituto de Astronomía, UNAM - IV Reunión sobre Astronomía Dinámica en Latinoamérica
Ed. Christine Allen, Alex Ruelas, & Ramachrisna Teixeira
a
b
No-GMCs
c
NEAR DISTANCE
RANDOM DISTANCE
Fig. 1. Heliocentric Longitude-Radius on plane Galactic distributions of CO. (a) Obtained from the integration of an
exponential disk with the central region evacuated plus an spiral pattern model (Luna 2003), a continuous distribution
without GMCs. (b) Obtained with GMCs associated to UC HII regions all them at near distances. (c) Obtained with
GMCs associated to UC HII regions with random selected near or far distance.
a
b
c
Fig. 2. Longitude-VelocityLSR distributions of CO. (a) Integrated CO intensity map from Dame et al. (2001). (b)
Obtained from the l-R distribution with an exponential disk with the central region evacuated plus an spiral pattern
model (Figure 1a) (c) Created from the l-R distribution based in a random selection of near and far distance (Figure 1c).
distance selection after 1000 models has a cross correlation average index of 0.80 and standard deviation
of 0.01.
Future Work: We intend to improve the radiative transfer model, the set of the UC HII regions
and the random normal distribution selection. Also
planned is the evaluation of the first Galactic quadrant, and the improvement of the GMC model intensity radial profile and size. We intend to implement
a selection criteria based on l-VLSR position by
minimizing a chi-square function, and to collect the
consistent results of the best models.
REFERENCES
Bronfman, L., Nyman, L.-Å., & May, J. 1996, A&AS,
115, 81
Dame, T., Hartmman, D., & Thadeuss, P. 2001, ApJ,
547, 792
Luna, A., 2003, PhD Thesis, INAOE, Mexico
Luna, A., Bronfman, L., Carrasco, L., & May, J. 2006,
ApJ, 641, 938